Thematische Bibliographien / Data-driven health services

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Auswahl der wissenschaftlichen Literatur zum Thema „Data-driven health services“

Autor: Grafiati

Veröffentlicht am 29. Juni 2021

Zuletzt aktualisiert am 1. Februar 2022

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Zeitschriftenartikel zum Thema "Data-driven health services"

Stefanini, Alessandro, Davide Aloini, Elisabetta Benevento, Riccardo Dulmin und Valeria Mininno. „A data-driven methodology for supporting resource planning of health services“. Socio-Economic Planning Sciences 70 (Juni 2020): 100744. http://dx.doi.org/10.1016/j.seps.2019.100744.

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IACOB, Nadina, und Felice SIMONELLI. „Towards a European Health Data Ecosystem“. European Journal of Risk Regulation 11, Nr. 4 (09.10.2020): 884–93. http://dx.doi.org/10.1017/err.2020.88.

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The digital health ecosystem is rife with opportunities to improve healthcare through data-driven services in the European Union (EU). The value of health data, in the multiple forms in which they come (from health records to lifestyle data collected by smartphones or wearables), can truly emerge when they are allowed to flow in the ecosystem within a governance framework supported by all relevant stakeholders, with trust as the common and clear thread underpinning it. The coronavirus pandemic has provided an additional impetus for change, showing the importance of coordination and adequate communication between Member States and quality data to inform decision-making. Significant challenges remain, however, in order to achieve a fully integrated European digital health ecosystem, including: (1) the potentially diverging rules set by Member States at the national level and the need for an EU framework for the secondary use of health data; (2) the need for transparency and accountability for sustaining a data-sharing framework involving public authorities, research organisations, industry and citizens; and (3) the need for interoperable data and processes. Taking stock of these challenges, this article puts forward policy recommendations to enable the provision of pan-European data-driven healthcare services and to build a transparent and trustworthy framework for citizens.

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Satinsky, Emily, Corine Driessens, David Crepaz-Keay und Antonis A. Kousoulis. „Mental health service users’ perceptions of data sharing and data protection: a short qualitative report“. BMJ Health & Care Informatics 25, Nr. 4 (Oktober 2018): 239–42. http://dx.doi.org/10.14236/jhi.v25i4.1033.

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BackgroundTo improve health services, social, economic and health data should be shared and linked to create a full narrative of lived experience. Mental health data sharing is often considered a particularly sensitive area.ObjectiveTo assess mental health service users’ perceptions regarding the current practice of administrative data-driven research.MethodWe conducted a focus group using case study scenarios. Themes and subthemes were analysed using qualitative methods.ResultsParticipants were generally happy for data owners to share their health, social and economic data if the purpose was transparent and if the information would inform and improve health policy and practice. Participants were less keen on sharing data through digital applications.ConclusionThis case study informs a data linkage study protocol. Research teams and database owners should strive to educate service users on data protection and create dissent opportunities.

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Birdthistle, Isolde J., Justin Fenty, Martine Collumbien, Charlotte Warren, James Kimani, Charity Ndwiga und Susannah Mayhew. „Integration of HIV and reproductive health services in public sector facilities: analysis of client flow data over time in Kenya“. BMJ Global Health 3, Nr. 5 (September 2018): e000867. http://dx.doi.org/10.1136/bmjgh-2018-000867.

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IntroductionIntegration of HIV/AIDS with reproductive health (RH) services can increase the uptake and efficiency of services, but gaps in knowledge remain about the practice of integration, particularly how provision can be expanded and performance enhanced. We assessed the extent and nature of service integration in public sector facilities in four districts in Kenya.MethodsBetween 2009 and 2012, client flow assessments were conducted at six time points in 24 government facilities, purposively selected as intervention or comparison sites. A total of 25 539 visits were tracked: 15 270 in districts where 6 of 12 facilities received an intervention to strengthen HIV service integration with family planning (FP); and 10 266 visits in districts where half the facilities received an HIV-postnatal care intervention in 2009–2010. We tracked the proportion of all visits in which: (1) an HIV service (testing, counselling or treatment) was received together with an RH service (FP counselling or provision, antenatal care, or postnatal care); (2) the client received HIV counselling.ResultsLevels of integrated HIV-RH services and HIV counselling were generally low across facilities and time points. An initial boost in integration was observed in most intervention sites, driven by integration of HIV services with FP counselling and provision, and declined after the first follow-up. Integration at most sites was driven by temporary rises in HIV counselling. The most consistent combination of HIV services was with antenatal care; the least common was with postnatal care.ConclusionsThese client flow data demonstrated a short-term boost in integration, after an initial intervention with FP services providing an opportunity to expand integration. Integration was not sustained over time highlighting the need for ongoing support. There are multiple opportunities for integrating service delivery, particularly within antenatal, FP and HIV counselling services, but a need for sustained systems and health worker support over time.Trial registration numberNCT01694862

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Walter, Angela Wangari, Randall P. Ellis und Yiyang Yuan. „Health care utilization and spending among privately insured children with medical complexity“. Journal of Child Health Care 23, Nr. 2 (19.07.2018): 213–31. http://dx.doi.org/10.1177/1367493518785778.

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Children with medical complexity have high health service utilization and health expenditures that can impose significant financial burdens. This study examined these issues for families with children enrolled in US private health plans. Using IBM Watson/Truven Analytics℠ MarketScan® commercial claims and encounters data (2012–2014), we analyzed through regression models, the differences in health care utilization and spending of disaggregated health care services by health plan types and children’s medical complexity levels. Children in consumer-driven and high-deductible plans had much higher out-of-pocket spending and cost shares than those in health maintenance organizations and preferred provider organizations (PPOs). Children with complex chronic conditions had higher service utilization and out-of-pocket expenditures while having lower cost shares on various categories of services than those without any chronic condition. Compared to families covered by PPOs, those with high-deductible or consumer-driven plans were 2.7 and 1.7 times more likely to spend over US$1000 out of pocket on their children’s medical care, respectively. Families with higher complexity levels were more likely to experience financial burdens from expenditures on children’s medical services. In conclusion, policymakers and families with children need to be cognizant of the significant financial burdens that can arise from children’s complex medical needs and health plan demand-side cost sharing.

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Stadnick, Nicole A., Anna S. Lau, Kelsey S. Dickson, Keri Pesanti, Debbie Innes-Gomberg und Lauren Brookman-Frazee. „Service use by youth with autism within a system-driven implementation of evidence-based practices in children’s mental health services“. Autism 24, Nr. 8 (18.07.2020): 2094–103. http://dx.doi.org/10.1177/1362361320934230.

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Public mental health systems play an important role in caring for youth with autism spectrum disorder. Like other dually diagnosed populations, youth with autism spectrum disorder may receive services in the context of evidence-based practice implementation efforts within public mental health systems. Little is known about service use patterns within the context of system-driven implementations efforts for this population. This case–control study examined mental health service patterns of 2537 youth with autism spectrum disorder compared to 2537 matched peers receiving care in the Los Angeles County Department of Mental Health, the largest public mental health department in the United States, within the context of a system-driven implementation of multiple evidence-based practices. Although not the primary target of this implementation effort, youth with autism spectrum disorder were served when they met criteria for the services based on their presenting mental health symptoms. Comparative analyses using administrative claims data were conducted to examine differences in mental health utilization patterns and clinical characteristics. Findings revealed significant differences in the volume and duration of mental health services as well as differences in the service type and evidence-based practice delivered between youth with and without autism spectrum disorder. Results provide direction targeting implementation efforts for youth with autism spectrum disorder within a public mental health system care reform.

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Simbolon, Pomarida, und Nagoklan Simbolon. „Association between Social-Cultural and the Utilization of Elderly Integrated Health Services (Posyandu Lansia) in Hamparan Perak Health Center“. Unnes Journal of Public Health 7, Nr. 1 (31.01.2018): 50–54. http://dx.doi.org/10.15294/ujph.v7i1.18201.

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Abstract Elderly Integrated Health Service (Posyandu Lansia) is an integrated service post for elderly in certain areas that have been agreed upon, which are community driven. A significant elderly population will be accompanied by various problems and will affect various aspects of life especially health. Based on preliminary data, the number of elderly population of 930 people, but only about 230 people or about 24.7% who came to Elderly Integrated Health Services. The purpose of this research was to analyze the association between socio-cultural and the utilization of Elderly Integrated Health Services. The type of this research is the explanatory survey with research population of 160 people and research sample of 60 respondents. Data collection used questionnaire. The results of this study were there was a correlation between tradition (p = 0.000), belief (0.001) with the utilization of Elderly Integrated Health Services. Abstrak Posyandu Lansia adalah pos pelayanan terpadu untuk orang tua di daerah tertentu yang telah disepakati, yang digerakkan oleh masyarakat. Populasi lansia yang signifikan akan disertai dengan berbagai masalah dan akan mempengaruhi berbagai aspek kehidupan khususnya kesehatan. Berdasarkan data awal jumlah populasi lansia sebanyak 930 orang tetapi yang datang ke posyandu lansia hanya berkisar 230 orang atau sekitar 24,7%. Tujuan dari penelitian ini adalah untuk menganalisis hubungan social budaya dengan pemanfaatan posyandu. Jenis penelitian ini adalah survey explanatory dengan populasi penelitian 160 orang dan sampel penelitian 60 responden. Pengumpulan data dengan menggunakan kuesioner. Hasil penelitian ini menunjukkan ada hubungan antara tradisi (p=0,000), kepercayaan (0,001) dengan dengan pemanfaatan Posyandu.

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Ozumba, Benjamin C., Nkechi G. Onyeneho, Malgorzata Chalupowski und S. V. Subramanian. „Inequities in Access to Maternal Health Care in Enugu State: Implications for Universal Health Coverage to Meet Vision 2030 in Nigeria“. International Quarterly of Community Health Education 39, Nr. 3 (24.12.2018): 163–73. http://dx.doi.org/10.1177/0272684x18819977.

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We explored the equity issues in access to maternal health services in Enugu State, Nigeria. We conducted a cross-sectional survey of 1,600 women who had babies within 6 months prior to the survey, drawn from four urban and rural local government areas in Enugu State of Nigeria, using structured questionnaire. Focus group discussions were held with grandmothers and fathers of the new babies. In-depth interviews were held with health workers. Results showed that inequities exist in access to quality health service when the mothers needed health care. The inequities in access to quality antenatal care (ANC) services were driven mainly by the type of localities of the mothers. Mothers who lived in the urban areas had better access ( p = .013). Other factors that facilitated access to better ANC services included being educated ( p = .049), being older ( p = .009), and belonging to the richer wealth quintile ( p < .001). With respect to access to health service when in need of health, differentials were seen with respect to living in urban residence ( p < .001), distance to the health facilities ( p < .001), and being rich ( p < .001). Access to health services was associated with odds ratio of 3.6 (95% CI [2.9, 4.4]) and 1.54 (95% CI [1.3, 2.0]) for living in urban residence and existence of good ANC service points, respectively. Similarly, living in urban areas was associated with an odds ratio of 1.3 (95% CI [1.1, 1.6]) of having access to good ANC services. These inequities in access to health service were also captured in the qualitative data. Suboptimal access to quality health care by segments of the populations poses challenge to universal health coverage in Enugu State. Action is needed to promote coordinated delivery of health services to ensure no one is left behind, irrespective of where they live or the socioeconomic strata they are born into.

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Korhonen, Olli, Karin Väyrynen, Tino Krautwald, Glenn Bilby, Hedwig Anna Theresia Broers, Guido Giunti und Minna Isomursu. „Data-Driven Personalization of a Physiotherapy Care Pathway: Case Study of Posture Scanning“. JMIR Rehabilitation and Assistive Technologies 7, Nr. 2 (15.09.2020): e18508. http://dx.doi.org/10.2196/18508.

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Background Advanced sensor, measurement, and analytics technologies are enabling entirely new ways to deliver health care. The increased availability of digital data can be used for data-driven personalization of care. Data-driven personalization can complement expert-driven personalization by providing support for decision making or even by automating some parts of decision making in relation to the care process. Objective The aim of this study was to analyze how digital data acquired from posture scanning can enhance physiotherapy services and enable more personalized delivery of physiotherapy. Methods A case study was conducted with a company that designed a posture scan recording system (PSRS), which is an information system that can digitally record, measure, and report human movement for use in physiotherapy. Data were collected through interviews with different stakeholders, such as health care professionals, health care users, and the information system provider, and were analyzed thematically. Results Based on the results of our thematic analysis, we propose three different types of support that posture scanning data can provide to enhance and enable more personalized delivery of physiotherapy: 1) modeling the condition, in which the posture scanning data are used to detect and understand the health care user’s condition and the root cause of the possible pain; 2) visualization for shared understanding, in which the posture scanning data are used to provide information to the health care user and involve them in more collaborative decision-making regarding their care; and 3) evaluating the impact of the intervention, in which the posture scanning data are used to evaluate the care progress and impact of the intervention. Conclusions The adoption of digital tools in physiotherapy has remained low. Physiotherapy has also lacked digital tools and means to inform and involve the health care user in their care in a person-centered manner. In this study, we gathered insights from different stakeholders to provide understanding of how the availability of digital posture scanning data can enhance and enable personalized physiotherapy services.

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Lanzoni, Gabriela Marcellino de Melo, Betina Hörner Schlindwein Meirelles, Alacoque Lorenzini Erdmann, Maira Buss Thofehrn und Clarice Maria Dall'Agnol. „ACTIONS/INTERACTIONS MOTIVATING NURSING LEADERSHIP IN THE CONTEXT OF PRIMARY HEALTH CARE“. Texto & Contexto - Enfermagem 24, Nr. 4 (24.11.2015): 1121–29. http://dx.doi.org/10.1590/0104-0707201500003740013.

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The aim of this qualitative study is to understand the actions/interactions identified as motivating leadership for nurses working at Primary Health Care services in a city in the South of Brazil. The Grounded Theory was used as the methodological framework. Data collection occurred through semi-structured interviews with twenty-three nurses working in the municipal health network and seven Nursing professors with expertise on the theme, distributed in four sample groups. The analysis revealed the category Composing the profile of nurses for leadership and its importance in health organizations, supported by three subcategories. The nurse exercises leadership driven by personality, vocational training stimulus, characteristics of the profession and influence of the environment. Nurses are influenced and influence the health service, acting in compliance with health policies, helping to foster the participation and integration of other workers in the health services.

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Dissertationen zum Thema "Data-driven health services"

Galozy, Alexander. „Data-driven personalized healthcare : Towards personalized interventions via reinforcement learning for Mobile Health“. Licentiate thesis, Högskolan i Halmstad, CAISR Centrum för tillämpade intelligenta system (IS-lab), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-44091.

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Medical and technological advancement in the last century has led to the unprecedented increase of the populace's quality of life and lifespan. As a result, an ever-increasing number of people live with chronic health conditions that require long-term treatment, resulting in increased healthcare costs and managerial burden to the healthcare provider. This increase in complexity can lead to ineffective decision-making and reduce care quality for the individual while increasing costs. One promising direction to tackle these issues is the active involvement of the patient in managing their care. Particularly for chronic diseases, where ongoing support is often required, patients must understand their illness and be empowered to manage their care. With the advent of smart devices such as smartphones, it is easier than ever to provide personalised digital interventions to patients, help them manage their treatment in their daily lives, and raise awareness about their illness. If such new approaches are to succeed, scalability is necessary, and solutions are needed that can act autonomously without costly human intervention. Furthermore, solutions should exhibit adaptability to the changing circumstances of an individual patient's health, needs and goals. Through the ongoing digitisation of healthcare, we are presented with the unique opportunity to develop cost-effective and scalable solutions through Artificial Intelligence (AI). This thesis presents work that we conducted as part of the project improving Medication Adherence through Person-Centered Care and Adaptive Interventions (iMedA) that aims to provide personalised adaptive interventions to hypertensive patients, supporting them in managing their medication regiment. The focus lies on inadequate medication adherence (MA), a pervasive issue where patients do not take their medication as instructed by their physician. The selection of individuals for intervention through secondary database analysis on Electronic Health Records (EHRs) was a key challenge and is addressed through in-depth analysis of common adherence measures, development of prediction models for MA and discussions on limitations of such approaches for analysing MA. Furthermore, providing personalised adaptive interventions is framed in the contextual bandit setting and addresses the challenge of delivering relevant interventions in environments where contextual information is significantly corrupted. The contributions of the thesis can be summarised as follows: (1) Highlighting the issues encountered in measuring MA through secondary database analysis and providing recommendations to address these issues, (2) Investigating machine learning models developed using EHRs for MA prediction and extraction of common refilling patterns through EHRs and (3) formal problem definition for a novel contextual bandit setting with context uncertainty commonly encountered in Mobile Health and development of an algorithm designed for such environments.

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Guerrero, Ludueña Richard E. „Data Driven Approach to Enhancing Efficiency and Value in Healthcare“. Doctoral thesis, Universitat de Barcelona, 2017. http://hdl.handle.net/10803/456670.

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Healthcare is changing, and the era of data-driven healthcare organisations is increasingly popular. Data-Driven approaches (e.g., Machine Learning, Metaheuristics, Modelling and Simulation, Data Analytics, and Data Visualisation) can be used to increase efficiency and value in health services. Despite extensive research and technological development, the evidence impact of those methodologies in the healthcare sector is limited. In this Thesis we argue that an approach without borders in terms of academic societies and field of study could help to tackle this lack of impact to enhance efficiency and value in healthcare. This Thesis is based on solving practical problems in healthcare, with the research drawing upon both theoretical and empirical analysis. The research is organised in four stages. In the first, a variety of techniques from Modelling and Simulation were studied and used to analyse current performance and to model improved and more efficient future states of healthcare systems. The focus was the analysis of capacity, demand, activity, and queues both at hospital and population levels. In the second part, a Genetic Algorithm was used to solve a Routing Home Healthcare problem. In the third part, Social Network Analysis was used to visualise and analyse email networks. In the final part, a new healthcare system performance metric is proposed and implemented using a case study. New frameworks to implement these methodologies in the context of real-world problems are presented throughout the Thesis. In collaboration with University of Southampton, Wessex Academic Health Science Network (AHSN), and NHS England, several projects were developed and implemented for healthcare improvement in the UK. The work aims to increase early detection of cancer and thereby reduce premature mortality. The research was conducted working closely with NHS organisations across the Wessex region in England to produce bespoke endoscopy service modelling, as well as population level models. At a regional level, a Colorectal Cancer Screening Programme model was developed. An analysis of endoscopy activity, capacity and demand across the region was conducted. Future demand for endoscopy services in five years' time was estimated, and we found that the system has enough capacity to attend the expected future activity. A new healthcare system performance metric is presented as a tool to improve healthcare services. Genetic Algorithm metaheuristic was applied in a variant of the Home Health Care Problem (HHCP), focusing on the route planning of clinical homecare. Working with the Hospital del Mar Medical Research Institute of Barcelona and the Agency of Health Quality and Assessment of Catalonia a study was developed to estimate future utilisation scenarios of knee arthroplasty (KA) revision in the Spanish National Health System in the short-term (2015) and long-term (2030) and their impact on primary KA utilisation. One of the findings was that the variation in the number of revisions depended on both the primary utilisation rate and the survival function applied. Future activity and resources needed was estimated. A Social Network Analysis (SNA) project was developed in collaboration with the Wessex AHSN to analyse and extract insight from an organisational email, using SNA and Data Mining. A new healthcare system performance metric - based on the Overall Equipment Effectiveness (OEE) measure - is proposed and evaluated using real data from and Endoscopy Unit from a UK based hospital. To summarise, this work identifies four key techniques to use in the investigation of health data - Machine Learning Algorithms, Metaheuristic, Discrete Event Simulation and Data Analytics & Visualisations. Following a review of the different subjects and associated issues, those four techniques were evaluated and used with an applied-focus to solve healthcare problems. Key learning points from all different studies, as well as challenges and opportunities for the application of data-driven methodologies are discussed in the final chapter of the Thesis.
La asistencia sanitaria está cambiando y la era de las organizaciones sanitarias basadas en datos es cada vez más popular. Los enfoques basados en datos (por ejemplo, Aprendizaje Automático; Meta-heurísticas; Modelamiento y Simulación; y Análisis y Visualización de datos) pueden utilizarse para aumentar la eficiencia y el valor en los servicios sanitarios. A pesar de la amplia investigación y el desarrollo tecnológico, la evidencia sobre el impacto de estas metodologías en el sector sanitario es limitada. En esta tesis argumentamos que un enfoque sin fronteras en términos de sociedades académicas y campo de estudio podría ayudar a abordar esta falta de impacto para aumentar la eficiencia y el valor en la asistencia sanitaria. Esta tesis se basa en la resolución de problemas prácticos en el sector sanitario, con un enfoque tanto teórico como práctico. La investigación se organizó en cuatro etapas. En la primera, una variedad de técnicas de modelamiento y simulación fueron estudiadas y aplicadas en el análisis y simulación de mejores y más eficientes configuraciones de sistemas sanitarios. El objetivo fue un análisis de capacidad, demanda, actividad y listas de esperas a nivel hospitalario y poblacional. En la segunda parte, un Algoritmo Genético fue implementado para resolver un problema de ruteo de personal sanitario encargado de atención de salud en el hogar. En la tercera parte, Análisis de Redes Sociales fue utilizado para visualizar y analizar una red de usuarios de correos electrónicos. En la etapa final, se propone una nueva métrica para evaluar el rendimiento de sistemas sanitarios, la cual fue implementada a través de un caso de estudio. Diferentes marcos de referencia para la implementación de estas metodologías en problemas reales se presentan a lo largo de la tesis.

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Fadul, Waad. „Data-Driven Health Services: an Empirical Investigation on the Role of Artificial Intelligence and Data Network Effects in Value Creation“. Thesis, Uppsala universitet, Informationssystem, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-447507.

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The purpose of this study is to produce new knowledge concerning the perceived user’s value generated using machine learning technologies that activate data network effects factors that create value through various business model themes. The data network effects theory represents a set of factors that increase the user’s perceived value for a platform that uses artificial intelligence capabilities. The study followed an abductive research approach where initially found facts were matched against the data network effects theory to be put in context and understood. The study’s data was gathered through semi-structured interviews with experts who were active within the research area and chosen based on their practical experience and their role in the digitization of the healthcare sector. The results show that three out of six factors were fully realized contributing to value creation while two of the factors showed to be partially realized in order to contribute to value creation and that is justified by the exclusion of users' perspectives in the scope of the research. Lastly, only one factor has limited contribution to the value creation due to the heavy regulations limiting its realization in the health sector. It is concluded that data network effects moderators contributed differently in the activation of various business model themes for value creation in a general manner where further studies should apply the theory in the assessment of one specific AI health offering to take full advantage of the theory potential. The theoretical implications showed that the data network factors may not necessarily be equally activated to contribute to value creation which was not initially highlighted by the theory. Additionally, the practical implications of the study’s results may help managers in their decision-making process on which factors to be activated for which business model theme.

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Chih, Meng-Chun, und 池孟純. „Ontological Knowledge Engine Driven Ubiquitous Web Service (UFIT) with HL7 based Health Data for Improving Physical Fitness“. Thesis, 2011. http://ndltd.ncl.edu.tw/handle/79437263460197366561.

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碩士
元智大學
工業工程與管理學系
99
The measures of health-related physical fitness provide assessment to five fitness components for a person: 1) cardiovascular endurance, 2) muscular endurance, 3) flexibility, 4) muscular strength, and 5) body composition. These measures serve as an important indicator for the health state of the person. The improvement of physical fitness generally leads to positive health-related physical fitness and makes the body less prone to common diseases. A personalized exercise plan that aids a balanced level of achievement in each of these fitness components is essential for an individual to maintain a healthy body. Nevertheless, inappropriate forms of exercise could lead to negative effects in terms of health-related physical fitness. This research aims to develop an ontology driven knowledge-based system for generating specifically designed exercise plan in accordance with user profile and user’s test data that involves Health Level Seven International (HL7)-based data of physical fitness and health screening. The generated plan can be accessed by using any Internet-enabled device through the paradigm of RESTful web service. In order to generate an exercise plan which is customized as well as pragmatic, the encapsulated knowledge used for inference in the system is acquired from the domain professionals. The system developed can serve not only as an intelligent system for improving physical fitness through generating personalized exercise plans but also as an UFIT for avoiding inappropriate work outs.

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Bücher zum Thema "Data-driven health services"

Madsen, Laura B. Data-Driven Healthcare: How Analytics and BI Are Transforming the Industry. Wiley & Sons, Incorporated, John, 2014.

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Madsen, Laura B. Data-Driven Healthcare: How Analytics and BI Are Transforming the Industry. Wiley & Sons, Incorporated, John, 2014.

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Data-Driven Healthcare: How Analytics and BI are Transforming the Industry. Wiley, 2014.

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van, José. Healthcare and Health Research. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190889760.003.0006.

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This chapter focuses on the platformization of the health sector. A burgeoning field of online health platforms has emerged, ranging from personal fitness apps to medical platforms that are used by patients, doctors, and researchers. A global industry of health-related platforms is being stacked onto, and interwoven with, the infrastructural core of the ecosystem; developing sectoral health platforms is a potentially lucrative and data-rich area that major operators are keen to invest in. Examining health platforms, the chapter unravels a peculiar double-edged logic in how their benefit is argued: they offer personalized data-driven services to their customers, while simultaneously serving an overarching public interest in medical research, the outcomes of which ostensibly benefit everyone. Using the platform mechanisms as an analytical prism, the chapter scrutinizes three single platforms, which are illustrative of the health sector: 23andMe, PatientsLikeMe, and Parkinson mPower.

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Gibson, Lorna M., Cathie L. M. Sudlow und Joanna M. Wardlaw. Incidental findings: Current ethical debates and future challenges in advanced neuroimaging. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198786832.003.0003.

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The urgency to pragmatically address the challenges of managing incidental findings on neuroimaging is driven by the recent development of very large, population-based imaging studies, and ever-increasing use of imaging within research, clinical, and commercial sectors. Incidental findings are complex and variable. Their clinical significance ranges from benign to life-threatening; detection may be influenced by imaging, reader, and participant characteristics; and feedback may generate follow-up and anxiety. Appropriate management of incidental findings is therefore challenging, but essential in order to minimize negative impacts on participants, health services, individual research studies, and public trust in the wider community. This chapter summarizes current knowledge of the scale of the problem of incidental findings, factors influencing detection, potential impact, and public expectations. It highlights areas where robust, empirical data are needed to inform the design of feasible management policies and improve informed consent processes for the future.

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Buchteile zum Thema "Data-driven health services"

Noyes, Katia, Fergal J. Fleming, James C. Iannuzzi und John R. T. Monson. „Health Services Information: Data-Driven Improvements in Surgical Quality: Structure, Process, and Outcomes“. In Health Services Evaluation, 141–70. New York, NY: Springer US, 2019. http://dx.doi.org/10.1007/978-1-4939-8715-3_8.

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Noyes, Katia, Fergal J. Fleming, James C. Iannuzzi und John R. T. Monson. „Health Services Information: Data-driven Improvements in Surgical Quality: Structure, Process, and Outcomes“. In Data and Measures in Health Services Research, 1–31. Boston, MA: Springer US, 2015. http://dx.doi.org/10.1007/978-1-4899-7673-4_8-1.

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Viswasam, Nikita, Justice Rivera, Carly Comins, Amrita Rao, Carrie E. Lyons und Stefan Baral. „The Epidemiology of HIV Among Sex Workers Around the World: Implications for Research, Programmes, and Policy“. In Sex Work, Health, and Human Rights, 15–39. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-64171-9_2.

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AbstractGlobally, sex workers of all genders and identities continue to face disproportionately high burdens of HIV, demonstrating the need for programmes better tailoring services to their unmet needs. The reasons for this high burden are complex, intersecting across behavioural, social, and structural realities experienced by sex workers. Here, we build on systematic reviews of HIV among sex workers and case studies rooted in sex workers’ lived experience to describe: (1) the global HIV burden among sex workers; (2) the factors and determinants that influence the HIV burden; (3) intervention coverage and gaps to reduce HIV-related inequities faced by sex workers, over the past decade.Sex workers living with HIV have not benefited enough from significant increases in HIV treatment among the general population. Engagement in this HIV treatment cascade is hindered by structural factors including stigma, migration, policing, criminalisation, and violence, as well as substance use, which present increasingly concurrent risks with HIV among sex workers.Emerging biomedical HIV prevention innovations exist to support the health and human rights of sex workers and reduce onward transmission risk, but persistent data gaps remain, and should be addressed via community-driven implementation research. Epidemiologic research engaging sex workers who are cismen and transgender persons is similarly crucial. Community empowerment approaches have reduced the odds of HIV infection, highlighting the case for greater investments in structural interventions. These investments, combined with filling data gaps and national action towards sex work decriminalisation alongside legal protections, are critical to achieving reductions in sex workers’ HIV burden.

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Beverley, Claire, und Manju Thakur. „Plantwise: A Knowledge and Intelligence Tool for Food Security through Crop Protection“. In Plant Diseases and Food Security in the 21st Century, 231–48. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-57899-2_11.

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AbstractFood security continues to be significantly impacted by a growing world population, changing climate, increasing food prices and environmental burden. One of the key challenges in reducing crop losses due to pests and diseases is timely delivery of appropriate, actionable extension advice to farmers. Information and communication technology (ICT) has the potential to improve services that connect smallholder farmers to new resources and information, helping to build their knowledge and ultimately improve their livelihoods. Such ICT-driven services have seen rapid growth over the past few years, and CABI has been harnessing this technology in several programmes. This chapter provides insight into digital interventions of the global, CABI-led programme, Plantwise, which aims to assist stakeholders in developing countries to improve their plant health systems by strengthening linkages among all actors involved, so that they can prevent and manage pest outbreaks more effectively. An overview of digital interventions piloted and tested under the umbrella of the Plantwise programme is illustrated with selected case studies. Interventions include pest diagnosis and management advice delivered via a website, plant health data collection, using a customized mobile application, and educational simulation games for ongoing support.

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Li, Yang, Chao Wu, Li Guo, Chun-Hsiang Lee und Yike Guo. „Wiki-Health“. In Cloud Computing Applications for Quality Health Care Delivery, 59–77. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-6118-9.ch004.

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Quickly evolving modern technologies such as cloud computing, Internet of things, and intelligent data analysis have created great opportunities for better living. The authors visualize the role these technological innovations will play in the healthcare sector as they spearhead a shift in focus from offering better healthcare services only to people with problems to helping everyone achieve a healthier lifestyle. In this chapter, the authors first discuss the existing and potential barriers followed by an in-depth demonstration of a service platform named Wiki-Health that takes advantage of cloud computing and Internet of things for personal well-being data management. It is a social platform, which is designed and implemented for data-driven and context-specific discovery of citizen communities in the areas of health, fitness, and well-being. At the end of the chapter, the authors analyse a case study to illustrate how the Wiki-Health platform can be used to serve a real world personal health training application.

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Sekar, Booma Devi, JiaLi Ma und MingChui Dong. „Wired and Wireless Distributed e-Home Healthcare System“. In Data Analytics in Medicine, 663–706. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1204-3.ch037.

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The proactive development in electronic health (e-health) has introduced seemingly endless number of applications such as telemedicine, electronic records, healthcare score cards, healthcare monitoring etc. Yet, these applications confront the key challenges of network dependence and medical personnel necessity, which hinders the development of universality of e-health services. To mitigate such key challenges, this chapter presents a versatile wired and wireless distributed e-home healthcare system. By exploiting the benefit of body sensor network and information communication technology, the dedicated system model methodically integrates some of the comprehensive functions such as pervasive health monitoring, remote healthcare data access, point-of-care signal interpretation and diagnosis, disease-driven uplink update and synchronization (UUS) scheme and emergency management to design a complete and independent e-home healthcare system.

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V., Uma, und Jayanthi Ganapathy. „Spatio-Temporal Hot Spot Analysis of Epidemic Diseases Using Geographic Information System for Improved Healthcare“. In Advances in Healthcare Information Systems and Administration, 31–63. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8470-4.ch002.

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Health-care systems aid in the diagnosis, treatment and prevention of diseases. Epidemiology deals with the demographic study on frequency, distribution and determinants of disease in order to provide better health-care. Today information technology has made data pervasive i.e. data is available anywhere and in abundance. GIS in epidemiology enables prompt services to mankind or people at risk. It brings out health-care services that are amicable for prevention and control of disease spread. This could be achieved when epidemiology data is modeled considering temporal and spatial factors and using data driven computation techniques over such models. This chapter discusses 1) the need for integrating GIS and epidemiology, 2) various case studies that indicates the need for spatial analysis being performed on epidemiologic data, 3) few techniques involved in the spatial analysis, 4) functionalities provided by some of the widely used GIS software packages and tools.

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Stachura, Maximillian E., Ellen B. Bolch, Katherine F. Piette und Joseph F. Ebberwein. „Chronic Condition Management Using Remote Monitoring and Telehomecare“. In Chronic Illness and Long-Term Care, 669–86. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7122-3.ch033.

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Individuals afflicted with multiple chronic conditions should be managed in real life settings and real time, while simultaneously reducing use of costly acute care services. New models of care delivery will enable patient participation in life-long care management programs and activities that target “wellness” while minimizing, delaying, or preventing clinical deterioration that requires hospitalization and/or visits to emergency care facilities. Successful care models will likely require new organizational and financial approaches that re-purpose health professional roles, responsibilities, and relationships. Remote monitoring and telehomecare technologies that employ advanced data management and analytic algorithms as well as dashboard displays of clinician- and services-relevant health information will support clinician decision-making at the point and time of care. Optimally, health professional financial incentives will be re-structured to support and sustain outcomes-driven long term chronic care that rewards efficiency and effectiveness. We present a work-in-progress model, RightHealthTM, including pilot project outcomes.

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Stachura, Maximillian E., Ellen B. Bolch, Katherine F. Piette und Joseph F. Ebberwein. „Chronic Condition Management Using Remote Monitoring and Telehomecare“. In Encyclopedia of Information Science and Technology, Third Edition, 3318–31. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-5888-2.ch326.

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Koledova, Ekaterina, Quentin Le Masne, Amalia Spataru, Merat Bagha und David Dixon. „Digital Health in the Management of Pediatric Growth Hormone Therapy – 10 Years of Developments“. In Studies in Health Technology and Informatics. IOS Press, 2021. http://dx.doi.org/10.3233/shti210314.

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Growth hormone administration is approved for use in a number of growth failure conditions in children. Optimal growth outcome requires continuous daily injections over many years, leading to problems of persistence and adherence with therapy. The easypod™ connect ecosystem enables electronic monitoring of injection and dose history, transmitted to a secure cloud database via the internet or cellular networks. Thus, healthcare providers can easily monitor adherence with therapy and be alerted to problems. The growlink™ patient app has been added to the ecosystem to provide solutions that can engage and educate patients and their families/caregivers. growlink™ also allows patients to self-report height and weight, enabling healthcare providers to track growth progression. The patient support program, TuiTek and the easypod™ Augmented Reality (AR) app are being developed within the ecosystem to support telehealth services, increase disease awareness and reduce therapy-related anxiety. easypod™ connect provides objective assessments of adherence, shown to be maintained at a high level over several years, and analyses showed that increased adherence was significantly associated with a better growth outcome. Studies have identified factors that influence persistence and adherence with GH therapy via the easypod™ connect ecosystem. These novel technologies are generating solutions that enable data-driven personalized care for children with growth disorders and optimize long-term clinical outcomes.

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Konferenzberichte zum Thema "Data-driven health services"

Stelmach, Pawel, und Lukasz Falas. „Runtime data-driven adaptation of composite e-Health services“. In 2013 IEEE 15th International Conference on e-Health Networking, Applications and Services (Healthcom 2013). IEEE, 2013. http://dx.doi.org/10.1109/healthcom.2013.6720644.

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Lee, C. S., A. Tiong, W. L. Tang und K. H. Yap. „Data-Driven “Market Basket”-Pricing and Personalized Health Information Services Using Salesforce's Model-Driven Systems Service Design“. In 2019 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2019. http://dx.doi.org/10.1109/ieem44572.2019.8978835.

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Naguri, Kausik, Poly Sil und Nandini Mukherjee. „Design of a health-data model and a query-driven implementation in Cassandra“. In 2015 17th International Conference on E-health Networking, Application & Services (HealthCom). IEEE, 2015. http://dx.doi.org/10.1109/healthcom.2015.7454488.

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Budilovsky, Oleksiy, Golnaz Alipour, Andre Knoesen, Lisa Brown und Soheil Ghiasi. „A data-driven approach to pre-operative evaluation of lung cancer patients“. In 2017 IEEE 19th International Conference on e-Health Networking, Applications and Services (Healthcom). IEEE, 2017. http://dx.doi.org/10.1109/healthcom.2017.8210810.

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Zhao, Chunyang, Seyedmostafa Hashemi, Peter Bach Andersen und Chresten Traholt. „Data-driven State of Health Modeling of Battery Energy Storage Systems Providing Grid Services“. In 2021 11th International Conference on Power, Energy and Electrical Engineering (CPEEE). IEEE, 2021. http://dx.doi.org/10.1109/cpeee51686.2021.9383356.

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Santamaria-Varas, Mar, und Pablo Martinez-Diez. „New Data-driven Analysis and Policies to Regulate Commerce and Tourism: The Examples of Barcelona and Madrid“. In 2018 ACSA International Conference. ACSA Press, 2018. http://dx.doi.org/10.35483/acsa.intl.2018.5.

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The regulation of economic activity is a question of the utmost relevance in urban planning as urbanism meants to support coexistence of citizens necessities while preserving the health of the commercial economic fabric. In this context, the model of diversity embodied by the city of Barcelona (paradigm of other European cities where commercial and leisure activities play a fundamental role in constructing the social, civic and economic values) is under discussion from the urban and political perspective. The saturation of public access activities, food retailers and tourist services -consequence of previous boosting liberal policies- is affecting the habitability and the quality of life of the residents. Using the new land-use plan of Ciutat Vella (Barcelona, Spain, 2018) as a case study, we intend to frame the regulation of public access and commercial activities in an international context, explain how this particular type of plan works and discuss the circumstances of its implementation.

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Lapira, Edzel R., Amit Deshpande, Jay Lee und John Snyder. „Smart Machine Health and Maintenance: Tool Assembly Prognostics“. In ASME 2008 International Manufacturing Science and Engineering Conference collocated with the 3rd JSME/ASME International Conference on Materials and Processing. ASMEDC, 2008. http://dx.doi.org/10.1115/msec_icmp2008-72314.

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It is well-established that unbalance in tool assembly causes excessive loads on spindle bearings and tool wear and increased vibration levels. However, in the days where high-speed machining (HSM) has become a common practice in the manufacturing industry, methodologies to measure tool assembly unbalance are not developed. In HSM the effects are worse, as the unbalance force is directly proportional to square of the spindle speed. Common practice in industry is to balance the tool assembly either with in-house balancing machines or use third-party balancing services after every batch cycle. This paper describes a data-driven methodology that detects the presence of unbalance in a tool assembly relative to the tools with known balance levels. The unbalance detection prognostic application developed as part of the Smart Machine Platform Initiative (SMPI) checks for the threshold unbalance level in the tool assembly for the given machining requirements before the start of any run. This approach uses statistical tools and a supervised learning algorithm based on the Watchdog Agent® toolbox developed by the Center for Intelligent Maintenance Systems. The proposed research finds high applicability in high-precision manufacturing operations involving high-volume production.

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Taweel, Adel, Stuart Speedie, Gareth Tyson, Abdel R. H. Tawil, Kevin Peterson und Brendan Delaney. „Service and model-driven dynamic integration of health data“. In the first international workshop. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2064747.2064752.

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Luís-Ferreira, Fernando, João Sarraipa, Jorge Calado, Joana Andrade, Daniel Rodrigues und Ricardo Jardim Goncalves. „Artificial Intelligence Based Architecture to Support Dementia Patients“. In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-10985.

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Abstract Artificial Intelligence is driving a revolution in the most diverse domains of computational services and user interaction. Data collected in large quantities is becoming useful for feeding intelligent systems that analyse, learn and provide insights and help decision support systems. Machine learning and the usage of algorithms are of most importance to extract features, reason over collected data so it becomes useful and preventive, exposing discoveries augmenting knowledge about systems and processes. Human driven applications, as those related with physiological assessment and user experience, are possible especially in the health domain and especially in supporting patients and the community. The work hereby described refers to different aspects where the Artificial Intelligence can help citizens and wraps a series devices and services that where developed and tested for the benefit of a special kind of citizens. The target population are those under some kind of Dementia, but the proposed solutions are also applicable to other elder citizens or even children that need to be assisted and prevented from risks.

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Jarwar, Muhammad Aslam, Sajjad Ali und Ilyoung Chong. „Exploring Web Objects enabled Data-Driven Microservices for E-Health Service Provision in IoT Environment“. In 2018 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2018. http://dx.doi.org/10.1109/ictc.2018.8539684.

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